sourabhshrivas/programmingassignment2

Repository for Programming Assignment 2 for R Programming on Coursera

Programming Assignment 2: Lexical Scoping For the Coursera course R Programming

The following code demonstrates how to use the Assessment3.R R script.

Lines starting with # are simple comments, lines starting with #> are things printed in the output.

read the R script

replace the "path/to/file" with the directory you save the file into

or you can read the file directly from the web

source("path/to/file/Assessment3.R")

create a square matrix (because solve only handles square matrices)

create the matrix during the call of makeCacheMatrix()

a <- makeCacheMatrix( matrix(c(1,2,12,13), nrow = 2, ncol = 2) );

summary(a); #> Length Class Mode
#> setMatrix 1 -none- function #> getMatrix 1 -none- function #> cacheInverse 1 -none- function #> getInverse 1 -none- function

a$getMatrix(); #> [,1] [,2] #> [1,] 1 12 #> [2,] 2 13

cacheSolve(a) #> [,1] [,2] #> [1,] -1.1818182 1.09090909 #> [2,] 0.1818182 -0.09090909

the 2nd time we run the function,we get the cached value

cacheSolve(a) #> getting cached data #> [,1] [,2] #> [1,] -1.1818182 1.09090909 #> [2,] 0.1818182 -0.09090909 Alternatively, the matrix can be created after calling a makeCacheMatrix without arguments.

read the R script

replace the "path/to/file" with the directory you save the file into

or you can read the file directly from the web

source("path/to/file/Assessment3.R")

call makeCacheMatrix without arguments

a <- makeCacheMatrix(); summary(a); #> Length Class Mode
#> setMatrix 1 -none- function #> getMatrix 1 -none- function #> cacheInverse 1 -none- function #> getInverse 1 -none- function

create a square matrix (reason solve only handles square matrices )

a$setMatrix( matrix(c(1,2,12,13), nrow = 2, ncol = 2) ); a$getMatrix(); #> [,1] [,2] #> [1,] 1 12 #> [2,] 2 13

cacheSolve(a) #> [,1] [,2] #> [1,] -1.1818182 1.09090909 #> [2,] 0.1818182 -0.09090909

the 2nd time we run the function, we get the cached value

cacheSolve(a) #> getting cached data #> [,1] [,2] #> [1,] -1.1818182 1.09090909 #> [2,] 0.1818182 -0.09090909